Golang Triplet.ToMatrix方法代码示例

func main() {

	// input matrix in Triplet format
	// including repeated positions. e.g. (0,0)
	var A la.Triplet
	A.Init(5, 5, 13)
	A.Put(0, 0, 1.0) // << repeated
	A.Put(0, 0, 1.0) // << repeated
	A.Put(1, 0, 3.0)
	A.Put(0, 1, 3.0)
	A.Put(2, 1, -1.0)
	A.Put(4, 1, 4.0)
	A.Put(1, 2, 4.0)
	A.Put(2, 2, -3.0)
	A.Put(3, 2, 1.0)
	A.Put(4, 2, 2.0)
	A.Put(2, 3, 2.0)
	A.Put(1, 4, 6.0)
	A.Put(4, 4, 1.0)

	// right-hand-side
	b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}

	// solve
	x, err := la.SolveRealLinSys(&A, b)
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// output
	la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
	la.PrintVec("b", b, "%v ", false)
	la.PrintVec("x", x, "%v ", false)
}

func main() {

	// input matrix in Triplet format
	// including repeated positions. e.g. (0,0)
	var A la.Triplet
	A.Init(5, 5, 13)
	A.Put(0, 0, 1.0) // << repeated
	A.Put(0, 0, 1.0) // << repeated
	A.Put(1, 0, 3.0)
	A.Put(0, 1, 3.0)
	A.Put(2, 1, -1.0)
	A.Put(4, 1, 4.0)
	A.Put(1, 2, 4.0)
	A.Put(2, 2, -3.0)
	A.Put(3, 2, 1.0)
	A.Put(4, 2, 2.0)
	A.Put(2, 3, 2.0)
	A.Put(1, 4, 6.0)
	A.Put(4, 4, 1.0)

	// right-hand-side
	b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}

	// allocate solver
	lis := la.GetSolver("umfpack")
	defer lis.Clean()

	// info
	symmetric := false
	verbose := false
	timing := false

	// initialise solver (R)eal
	err := lis.InitR(&A, symmetric, verbose, timing)
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// factorise
	err = lis.Fact()
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// solve (R)eal
	var dummy bool
	x := make([]float64, len(b))
	err = lis.SolveR(x, b, dummy) // x := inv(a) * b
	if err != nil {
		io.Pfred("solver failed:\n%v", err)
		return
	}

	// output
	la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
	la.PrintVec("b", b, "%v ", false)
	la.PrintVec("x", x, "%v ", false)
}

func CompareJac(tst *testing.T, ffcn Cb_f, Jfcn Cb_J, x []float64, tol float64, distr bool) {
	n := len(x)
	// numerical
	fx := make([]float64, n)
	w := make([]float64, n) // workspace
	ffcn(fx, x)
	var Jnum la.Triplet
	Jnum.Init(n, n, n*n)
	Jacobian(&Jnum, ffcn, x, fx, w, distr)
	jn := Jnum.ToMatrix(nil)
	// analytical
	var Jana la.Triplet
	Jana.Init(n, n, n*n)
	Jfcn(&Jana, x)
	ja := Jana.ToMatrix(nil)
	// compare
	//la.PrintMat(fmt.Sprintf("Jana(%d)",mpi.Rank()), ja.ToDense(), "%13.6f", false)
	//la.PrintMat(fmt.Sprintf("Jnum(%d)",mpi.Rank()), jn.ToDense(), "%13.6f", false)
	max_diff := la.MatMaxDiff(jn.ToDense(), ja.ToDense())
	if max_diff > tol {
		tst.Errorf("[1;31mmax_diff = %g[0m\n", max_diff)
	} else {
		io.Pf("[1;32mmax_diff = %g[0m\n", max_diff)
	}
}

// CompareJacMpi compares Jacobian matrix (e.g. for testing)
func CompareJacMpi(tst *testing.T, ffcn Cb_f, Jfcn Cb_J, x []float64, tol float64, distr bool) {

	// numerical
	n := len(x)
	fx := make([]float64, n)
	w := make([]float64, n) // workspace
	ffcn(fx, x)
	var Jnum la.Triplet
	Jnum.Init(n, n, n*n)
	JacobianMpi(&Jnum, ffcn, x, fx, w, distr)
	jn := Jnum.ToMatrix(nil)

	// analytical
	var Jana la.Triplet
	Jana.Init(n, n, n*n)
	Jfcn(&Jana, x)
	ja := Jana.ToMatrix(nil)

	// compare
	max_diff := la.MatMaxDiff(jn.ToDense(), ja.ToDense())
	if max_diff > tol {
		tst.Errorf("[1;31mmax_diff = %g[0m\n", max_diff)
	} else {
		io.Pf("[1;32mmax_diff = %g[0m\n", max_diff)
	}
}

// CheckJ check Jacobian matrix
//  Ouptut: cnd -- condition number (with Frobenius norm)
func (o *NlSolver) CheckJ(x []float64, tol float64, chkJnum, silent bool) (cnd float64, err error) {

	// Jacobian matrix
	var Jmat [][]float64
	if o.useDn {
		Jmat = la.MatAlloc(o.neq, o.neq)
		err = o.JfcnDn(Jmat, x)
		if err != nil {
			return 0, chk.Err(_nls_err5, "dense", err.Error())
		}
	} else {
		if o.numJ {
			err = Jacobian(&o.Jtri, o.Ffcn, x, o.fx, o.w, false)
			if err != nil {
				return 0, chk.Err(_nls_err5, "sparse", err.Error())
			}
		} else {
			err = o.JfcnSp(&o.Jtri, x)
			if err != nil {
				return 0, chk.Err(_nls_err5, "sparse(num)", err.Error())
			}
		}
		Jmat = o.Jtri.ToMatrix(nil).ToDense()
	}
	//la.PrintMat("J", Jmat, "%23g", false)

	// condition number
	cnd, err = la.MatCondG(Jmat, "F", 1e-10)
	if err != nil {
		return cnd, chk.Err(_nls_err6, err.Error())
	}
	if math.IsInf(cnd, 0) || math.IsNaN(cnd) {
		return cnd, chk.Err(_nls_err7, cnd)
	}

	// numerical Jacobian
	if !chkJnum {
		return
	}
	var Jtmp la.Triplet
	ws := make([]float64, o.neq)
	err = o.Ffcn(o.fx, x)
	if err != nil {
		return
	}
	Jtmp.Init(o.neq, o.neq, o.neq*o.neq)
	Jacobian(&Jtmp, o.Ffcn, x, o.fx, ws, false)
	Jnum := Jtmp.ToMatrix(nil).ToDense()
	for i := 0; i < o.neq; i++ {
		for j := 0; j < o.neq; j++ {
			chk.PrintAnaNum(io.Sf("J[%d][%d]", i, j), tol, Jmat[i][j], Jnum[i][j], !silent)
		}
	}
	maxdiff := la.MatMaxDiff(Jmat, Jnum)
	if maxdiff > tol {
		err = chk.Err(_nls_err8, maxdiff)
	}
	return
}

func main() {

	mpi.Start(false)
	defer func() {
		mpi.Stop(false)
	}()

	if mpi.Rank() == 0 {
		chk.PrintTitle("Test SumToRoot 01")
	}

	M := [][]float64{
		{1000, 1000, 1000, 1011, 1021, 1000},
		{1000, 1000, 1000, 1012, 1022, 1000},
		{1000, 1000, 1000, 1013, 1023, 1000},
		{1011, 1012, 1013, 1000, 1000, 1000},
		{1021, 1022, 1023, 1000, 1000, 1000},
		{1000, 1000, 1000, 1000, 1000, 1000},
	}

	id, sz, m := mpi.Rank(), mpi.Size(), len(M)
	start, endp1 := (id*m)/sz, ((id+1)*m)/sz

	if sz > 6 {
		chk.Panic("this test works with at most 6 processors")
	}

	var J la.Triplet
	J.Init(m, m, m*m)
	for i := start; i < endp1; i++ {
		for j := 0; j < m; j++ {
			J.Put(i, j, M[i][j])
		}
	}
	la.PrintMat(fmt.Sprintf("J @ proc # %d", id), J.ToMatrix(nil).ToDense(), "%10.1f", false)

	la.SpTriSumToRoot(&J)
	var tst testing.T
	if mpi.Rank() == 0 {
		chk.Matrix(&tst, "J @ proc 0", 1.0e-17, J.ToMatrix(nil).ToDense(), [][]float64{
			{1000, 1000, 1000, 1011, 1021, 1000},
			{1000, 1000, 1000, 1012, 1022, 1000},
			{1000, 1000, 1000, 1013, 1023, 1000},
			{1011, 1012, 1013, 1000, 1000, 1000},
			{1021, 1022, 1023, 1000, 1000, 1000},
			{1000, 1000, 1000, 1000, 1000, 1000},
		})
	}
}

func Test_assemb01(tst *testing.T) {

	chk.PrintTitle("assemb01")

	// grid
	var g Grid2D
	g.Init(1.0, 1.0, 3, 3)

	// equations numbering
	var e Equations
	e.Init(g.N, []int{0, 3, 6})

	// K11 and K12
	var K11, K12 la.Triplet
	InitK11andK12(&K11, &K12, &e)

	// assembly
	F1 := make([]float64, e.N1)
	Assemble(&K11, &K12, F1, nil, &g, &e)

	// check
	K11d := K11.ToMatrix(nil).ToDense()
	K12d := K12.ToMatrix(nil).ToDense()
	K11c := [][]float64{
		{16.0, -4.0, -8.0, 0.0, 0.0, 0.0},
		{-8.0, 16.0, 0.0, -8.0, 0.0, 0.0},
		{-4.0, 0.0, 16.0, -4.0, -4.0, 0.0},
		{0.0, -4.0, -8.0, 16.0, 0.0, -4.0},
		{0.0, 0.0, -8.0, 0.0, 16.0, -4.0},
		{0.0, 0.0, 0.0, -8.0, -8.0, 16.0},
	}
	K12c := [][]float64{
		{-4.0, 0.0, 0.0},
		{0.0, 0.0, 0.0},
		{0.0, -4.0, 0.0},
		{0.0, 0.0, 0.0},
		{0.0, 0.0, -4.0},
		{0.0, 0.0, 0.0},
	}
	chk.Matrix(tst, "K11: ", 1e-16, K11d, K11c)
	chk.Matrix(tst, "K12: ", 1e-16, K12d, K12c)
}

func TestJacobian03(tst *testing.T) {

	//verbose()
	chk.PrintTitle("TestJacobian 03")

	// grid
	var g fdm.Grid2D
	//g.Init(1.0, 1.0, 4, 4)
	g.Init(1.0, 1.0, 6, 6)
	//g.Init(1.0, 1.0, 11, 11)

	// equations numbering
	var e fdm.Equations
	peq := utl.IntUnique(g.L, g.R, g.B, g.T)
	e.Init(g.N, peq)

	// K11 and K12
	var K11, K12 la.Triplet
	fdm.InitK11andK12(&K11, &K12, &e)

	// assembly
	F1 := make([]float64, e.N1)
	fdm.Assemble(&K11, &K12, F1, nil, &g, &e)

	// prescribed values
	U2 := make([]float64, e.N2)
	for _, eq := range g.L {
		U2[e.FR2[eq]] = 50.0
	}
	for _, eq := range g.R {
		U2[e.FR2[eq]] = 0.0
	}
	for _, eq := range g.B {
		U2[e.FR2[eq]] = 0.0
	}
	for _, eq := range g.T {
		U2[e.FR2[eq]] = 50.0
	}

	// functions
	k11 := K11.ToMatrix(nil)
	k12 := K12.ToMatrix(nil)
	ffcn := func(fU1, U1 []float64) error { // K11*U1 + K12*U2 - F1
		la.VecCopy(fU1, -1, F1)            // fU1 := (-F1)
		la.SpMatVecMulAdd(fU1, 1, k11, U1) // fU1 += K11*U1
		la.SpMatVecMulAdd(fU1, 1, k12, U2) // fU1 += K12*U2
		return nil
	}
	Jfcn := func(dfU1dU1 *la.Triplet, U1 []float64) error {
		fdm.Assemble(dfU1dU1, &K12, F1, nil, &g, &e)
		return nil
	}
	U1 := make([]float64, e.N1)
	CompareJac(tst, ffcn, Jfcn, U1, 0.0075)

	print_jac := false
	if print_jac {
		W1 := make([]float64, e.N1)
		fU1 := make([]float64, e.N1)
		ffcn(fU1, U1)
		var Jnum la.Triplet
		Jnum.Init(e.N1, e.N1, e.N1*e.N1)
		Jacobian(&Jnum, ffcn, U1, fU1, W1)
		la.PrintMat("K11 ", K11.ToMatrix(nil).ToDense(), "%g ", false)
		la.PrintMat("Jnum", Jnum.ToMatrix(nil).ToDense(), "%g ", false)
	}

	test_ffcn := false
	if test_ffcn {
		Uc := []float64{0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0, 25.0, 325.0 / 22.0, 100.0 / 11.0, 50.0 / 11.0,
			0.0, 50.0, 775.0 / 22.0, 25.0, 375.0 / 22.0, 100.0 / 11.0, 0.0, 50.0, 450.0 / 11.0, 725.0 / 22.0,
			25.0, 325.0 / 22.0, 0.0, 50.0, 500.0 / 11.0, 450.0 / 11.0, 775.0 / 22.0, 25.0, 0.0, 50.0, 50.0,
			50.0, 50.0, 50.0, 50.0,
		}
		for i := 0; i < e.N1; i++ {
			U1[i] = Uc[e.RF1[i]]
		}
		fU1 := make([]float64, e.N1)
		min, max := la.VecMinMax(fU1)
		io.Pf("min/max fU1 = %v\n", min, max)
	}
}

func TestDiffusion1D(tst *testing.T) {

	//verbose()
	chk.PrintTitle("Test Diffusion 1D (cooling)")

	// solution parameters
	silent := false
	fixstp := true
	//fixstp := false
	//method := "FwEuler"
	method := "BwEuler"
	//method := "Dopri5"
	//method := "Radau5"
	//numjac := true
	numjac := false
	rtol := 1e-4
	atol := rtol

	// timestep
	t0, tf, dt := 0.0, 0.2, 0.03

	// problem data
	kx := 1.0 // conductivity
	N := 6    // number of nodes
	//Nb   := N + 2             // augmented system dimension
	xmax := 1.0               // length
	dx := xmax / float64(N-1) // spatial step size
	dxx := dx * dx
	mol := []float64{kx / dxx, -2.0 * kx / dxx, kx / dxx}

	// function
	fcn := func(f []float64, t float64, y []float64, args ...interface{}) error {
		for i := 0; i < N; i++ {
			f[i] = 0
			if i == 0 || i == N-1 {
				continue // skip presc node
			}
			for p, j := range []int{i - 1, i, i + 1} {
				if j < 0 {
					j = i + 1
				} //  left boundary
				if j == N {
					j = i - 1
				} //  right boundary
				f[i] += mol[p] * y[j]
			}
		}
		//io.Pfgrey("y = %v\n", y)
		//io.Pfcyan("f = %v\n", f)
		return nil
	}

	// Jacobian
	jac := func(dfdy *la.Triplet, t float64, y []float64, args ...interface{}) error {
		//chk.Panic("jac is not available")
		if dfdy.Max() == 0 {
			//dfdy.Init(Nb, Nb, 3*N)
			dfdy.Init(N, N, 3*N)
		}
		dfdy.Start()
		for i := 0; i < N; i++ {
			if i == 0 || i == N-1 {
				dfdy.Put(i, i, 0.0)
				continue
			}
			for p, j := range []int{i - 1, i, i + 1} {
				if j < 0 {
					j = i + 1
				} //  left boundary
				if j == N {
					j = i - 1
				} //  right boundary
				dfdy.Put(i, j, mol[p])
			}
		}
		return nil
	}

	// initial values
	x := utl.LinSpace(0.0, xmax, N)
	y := make([]float64, N)
	//y := make([]float64, Nb)
	for i := 0; i < N; i++ {
		y[i] = 4.0*x[i] - 4.0*x[i]*x[i]
	}

	// debug
	f0 := make([]float64, N)
	//f0 := make([]float64, Nb)
	fcn(f0, 0, y)
	if false {
		io.Pforan("y0 = %v\n", y)
		io.Pforan("f0 = %v\n", f0)
		var J la.Triplet
		jac(&J, 0, y)
		la.PrintMat("J", J.ToMatrix(nil).ToDense(), "%8.3f", false)
	}
	//chk.Panic("stop")

	/*
//.........这里部分代码省略.........

func Test_nls04(tst *testing.T) {

	//verbose()
	chk.PrintTitle("nls04. finite differences problem")

	// grid
	var g fdm.Grid2D
	g.Init(1.0, 1.0, 6, 6)

	// equations numbering
	var e fdm.Equations
	peq := utl.IntUnique(g.L, g.R, g.B, g.T)
	e.Init(g.N, peq)

	// K11 and K12
	var K11, K12 la.Triplet
	fdm.InitK11andK12(&K11, &K12, &e)

	// assembly
	F1 := make([]float64, e.N1)
	fdm.Assemble(&K11, &K12, F1, nil, &g, &e)

	// prescribed values
	U2 := make([]float64, e.N2)
	for _, eq := range g.L {
		U2[e.FR2[eq]] = 50.0
	}
	for _, eq := range g.R {
		U2[e.FR2[eq]] = 0.0
	}
	for _, eq := range g.B {
		U2[e.FR2[eq]] = 0.0
	}
	for _, eq := range g.T {
		U2[e.FR2[eq]] = 50.0
	}

	// functions
	k11 := K11.ToMatrix(nil)
	k12 := K12.ToMatrix(nil)
	ffcn := func(fU1, U1 []float64) error { // K11*U1 + K12*U2 - F1
		la.VecCopy(fU1, -1, F1)            // fU1 := (-F1)
		la.SpMatVecMulAdd(fU1, 1, k11, U1) // fU1 += K11*U1
		la.SpMatVecMulAdd(fU1, 1, k12, U2) // fU1 += K12*U2
		return nil
	}
	Jfcn := func(dfU1dU1 *la.Triplet, U1 []float64) error {
		fdm.Assemble(dfU1dU1, &K12, F1, nil, &g, &e)
		return nil
	}
	JfcnD := func(dfU1dU1 [][]float64, U1 []float64) error {
		la.MatCopy(dfU1dU1, 1, K11.ToMatrix(nil).ToDense())
		return nil
	}

	prms := map[string]float64{
		"atol":    1e-8,
		"rtol":    1e-8,
		"ftol":    1e-12,
		"lSearch": 0.0,
	}

	// init
	var nls_sps NlSolver // sparse analytical
	var nls_num NlSolver // sparse numerical
	var nls_den NlSolver // dense analytical
	nls_sps.Init(e.N1, ffcn, Jfcn, nil, false, false, prms)
	nls_num.Init(e.N1, ffcn, nil, nil, false, true, prms)
	nls_den.Init(e.N1, ffcn, nil, JfcnD, true, false, prms)
	defer nls_sps.Clean()
	defer nls_num.Clean()
	defer nls_den.Clean()

	// results
	U1sps := make([]float64, e.N1)
	U1num := make([]float64, e.N1)
	U1den := make([]float64, e.N1)
	Usps := make([]float64, e.N)
	Unum := make([]float64, e.N)
	Uden := make([]float64, e.N)

	// solution
	Uc := []float64{0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0, 25.0, 325.0 / 22.0, 100.0 / 11.0, 50.0 / 11.0,
		0.0, 50.0, 775.0 / 22.0, 25.0, 375.0 / 22.0, 100.0 / 11.0, 0.0, 50.0, 450.0 / 11.0, 725.0 / 22.0,
		25.0, 325.0 / 22.0, 0.0, 50.0, 500.0 / 11.0, 450.0 / 11.0, 775.0 / 22.0, 25.0, 0.0, 50.0, 50.0,
		50.0, 50.0, 50.0, 50.0,
	}

	io.PfYel("\n---- sparse -------- Analytical Jacobian -------------------\n")

	// solve
	err := nls_sps.Solve(U1sps, false)
	if err != nil {
		chk.Panic(err.Error())
	}

	// check
	fdm.JoinVecs(Usps, U1sps, U2, &e)
	chk.Vector(tst, "Usps", 1e-14, Usps, Uc)

//.........这里部分代码省略.........

func Test_linipm02(tst *testing.T) {

	//verbose()
	chk.PrintTitle("linipm02")

	// linear program
	//   min   2*x0 +   x1
	//   s.t.   -x0 +   x1 ≤ 1
	//           x0 +   x1 ≥ 2   →  -x0 - x1 ≤ -2
	//           x0 - 2*x1 ≤ 4
	//         x1 ≥ 0
	// standard (step 1) add slack
	//   s.t.   -x0 +   x1 + x2           = 1
	//          -x0 -   x1      + x3      = -2
	//           x0 - 2*x1           + x4 = 4
	// standard (step 2)
	//    replace x0 := x0_ - x5
	//    because it's unbounded
	//    min  2*x0_ +   x1                - 2*x5
	//    s.t.  -x0_ +   x1 + x2           +   x5 = 1
	//          -x0_ -   x1      + x3      +   x5 = -2
	//           x0_ - 2*x1           + x4 -   x5 = 4
	//         x0_,x1,x2,x3,x4,x5 ≥ 0
	var T la.Triplet
	T.Init(3, 6, 12)
	T.Put(0, 0, -1)
	T.Put(0, 1, 1)
	T.Put(0, 2, 1)
	T.Put(0, 5, 1)
	T.Put(1, 0, -1)
	T.Put(1, 1, -1)
	T.Put(1, 3, 1)
	T.Put(1, 5, 1)
	T.Put(2, 0, 1)
	T.Put(2, 1, -2)
	T.Put(2, 4, 1)
	T.Put(2, 5, -1)
	Am := T.ToMatrix(nil)
	A := Am.ToDense()
	c := []float64{2, 1, 0, 0, 0, -2}
	b := []float64{1, -2, 4}

	// print LP
	la.PrintMat("A", A, "%6g", false)
	la.PrintVec("b", b, "%6g", false)
	la.PrintVec("c", c, "%6g", false)
	io.Pf("\n")

	// solve LP
	var ipm LinIpm
	defer ipm.Clean()
	ipm.Init(Am, b, c, nil)
	err := ipm.Solve(chk.Verbose)
	if err != nil {
		tst.Errorf("ipm failed:\n%v", err)
		return
	}

	// check
	io.Pf("\n")
	bres := make([]float64, len(b))
	la.MatVecMul(bres, 1, A, ipm.X)
	io.Pforan("bres = %v\n", bres)
	chk.Vector(tst, "A*x=b", 1e-8, bres, b)

	// fix and check x
	x := ipm.X[:2]
	x[0] -= ipm.X[5]
	io.Pforan("x = %v\n", x)
	chk.Vector(tst, "x", 1e-8, x, []float64{0.5, 1.5})

	// plot
	if true && chk.Verbose {
		f := func(x []float64) float64 {
			return c[0]*x[0] + c[1]*x[1]
		}
		g := func(x []float64, i int) float64 {
			return A[i][0]*x[0] + A[i][1]*x[1] - b[i]
		}
		np := 41
		vmin, vmax := []float64{-2.0, -2.0}, []float64{2.0, 2.0}
		PlotTwoVarsContour("/tmp/gosl", "test_linipm02", x, np, nil, true, vmin, vmax, f,
			func(x []float64) float64 { return g(x, 0) },
			func(x []float64) float64 { return g(x, 1) },
		)
	}
}

func Test_linipm01(tst *testing.T) {

	//verbose()
	chk.PrintTitle("linipm01")

	// linear programming problem
	//   min  -4*x0 - 5*x1
	//   s.t.  2*x0 +   x1 ≤ 3
	//           x0 + 2*x1 ≤ 3
	//         x0,x1 ≥ 0
	// standard:
	//         2*x0 +   x1 + x2     = 3
	//           x0 + 2*x1     + x3 = 3
	//         x0,x1,x2,x3 ≥ 0
	var T la.Triplet
	T.Init(2, 4, 6)
	T.Put(0, 0, 2.0)
	T.Put(0, 1, 1.0)
	T.Put(0, 2, 1.0)
	T.Put(1, 0, 1.0)
	T.Put(1, 1, 2.0)
	T.Put(1, 3, 1.0)
	Am := T.ToMatrix(nil)
	A := Am.ToDense()
	c := []float64{-4, -5, 0, 0}
	b := []float64{3, 3}

	// print LP
	la.PrintMat("A", A, "%6g", false)
	la.PrintVec("b", b, "%6g", false)
	la.PrintVec("c", c, "%6g", false)
	io.Pf("\n")

	// solve LP
	var ipm LinIpm
	defer ipm.Clean()
	ipm.Init(Am, b, c, nil)
	err := ipm.Solve(chk.Verbose)
	if err != nil {
		tst.Errorf("ipm failed:\n%v", err)
		return
	}

	// check
	io.Pf("\n")
	io.Pforan("x = %v\n", ipm.X)
	io.Pfcyan("λ = %v\n", ipm.L)
	io.Pforan("s = %v\n", ipm.S)
	x := ipm.X[:2]
	bres := make([]float64, 2)
	la.MatVecMul(bres, 1, A, x)
	io.Pforan("bres = %v\n", bres)
	chk.Vector(tst, "x", 1e-9, x, []float64{1, 1})
	chk.Vector(tst, "A*x=b", 1e-8, bres, b)

	// plot
	if true && chk.Verbose {
		f := func(x []float64) float64 {
			return c[0]*x[0] + c[1]*x[1]
		}
		g := func(x []float64, i int) float64 {
			return A[i][0]*x[0] + A[i][1]*x[1] - b[i]
		}
		np := 41
		vmin, vmax := []float64{-2.0, -2.0}, []float64{2.0, 2.0}
		PlotTwoVarsContour("/tmp/gosl", "test_linipm01", x, np, nil, true, vmin, vmax, f,
			func(x []float64) float64 { return g(x, 0) },
			func(x []float64) float64 { return g(x, 1) },
		)
	}
}